Multi-energy microgrid optimal operation

With the increasing demand for global energy, multi-energy microgrids have drawn more attention in recent years. In a multi-energy microgrid (MEMG), different kinds of energies like heat, electricity, cooling, and gas are interacted with each at various levels, aiming to increase the overall energy...

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Main Author: Chen, Yumin
Other Authors: Xu Yan
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2020
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Online Access:https://hdl.handle.net/10356/136774
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1367742023-07-04T17:15:13Z Multi-energy microgrid optimal operation Chen, Yumin Xu Yan School of Electrical and Electronic Engineering XUYAN@ntu.edu.sg Engineering::Electrical and electronic engineering::Electric power With the increasing demand for global energy, multi-energy microgrids have drawn more attention in recent years. In a multi-energy microgrid (MEMG), different kinds of energies like heat, electricity, cooling, and gas are interacted with each at various levels, aiming to increase the overall energy utilization efficiency. MEMG usually contains many different generation units and ancillary components like combined heat and power (CHP) plant, photovoltaic cell (PV), wind turbine (WT), electric boiler (EB), fuel cell (FC), energy storage (ES) and so on. Since the operational properties and technical limits are quite different, how to optimally dispatch these units is a key research topic in this area. Besides, the properties of these energy networks are also different. For instance, we usually assume that electricity can be delivered to customers immediately without any time delay. However, in the heat network, thermal energy is transferred by hot water in pipes. Since the flow rate of hot water is much slower than the transmission speed of electricity, there is a transmission delay ranging from minutes to hours in the heat network. Thus, it is valuable to consider the transferring time delay in MEMG. What’s more, the uncertainties of renewable energy resources pose a significant challenge to the operation of MEMG. The focus of this research topic is to propose a suitable coordinated operation method for MEMG with coupled heat and electrical networks, in which the specific models of electrical network and heat network are systematically studied. Further, demand response management (DRM) and the randomness of renewable energy resources are considered in the proposed method to better operate MEMG. All the proposed operation and planning methods have been verified in simulation using GAMS and HOMER. The proposed method is simulated on a MEMG with coupled heat and electrical network, which is based on the IEEE 33-bus radial distribution network and a 13-pipe DHN. Master of Engineering 2020-01-24T01:59:44Z 2020-01-24T01:59:44Z 2019 Thesis-Master by Research Chen, Y. (2019). Multi-energy microgrid optimal operation. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/136774 10.32657/10356/136774 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Electric power
spellingShingle Engineering::Electrical and electronic engineering::Electric power
Chen, Yumin
Multi-energy microgrid optimal operation
description With the increasing demand for global energy, multi-energy microgrids have drawn more attention in recent years. In a multi-energy microgrid (MEMG), different kinds of energies like heat, electricity, cooling, and gas are interacted with each at various levels, aiming to increase the overall energy utilization efficiency. MEMG usually contains many different generation units and ancillary components like combined heat and power (CHP) plant, photovoltaic cell (PV), wind turbine (WT), electric boiler (EB), fuel cell (FC), energy storage (ES) and so on. Since the operational properties and technical limits are quite different, how to optimally dispatch these units is a key research topic in this area. Besides, the properties of these energy networks are also different. For instance, we usually assume that electricity can be delivered to customers immediately without any time delay. However, in the heat network, thermal energy is transferred by hot water in pipes. Since the flow rate of hot water is much slower than the transmission speed of electricity, there is a transmission delay ranging from minutes to hours in the heat network. Thus, it is valuable to consider the transferring time delay in MEMG. What’s more, the uncertainties of renewable energy resources pose a significant challenge to the operation of MEMG. The focus of this research topic is to propose a suitable coordinated operation method for MEMG with coupled heat and electrical networks, in which the specific models of electrical network and heat network are systematically studied. Further, demand response management (DRM) and the randomness of renewable energy resources are considered in the proposed method to better operate MEMG. All the proposed operation and planning methods have been verified in simulation using GAMS and HOMER. The proposed method is simulated on a MEMG with coupled heat and electrical network, which is based on the IEEE 33-bus radial distribution network and a 13-pipe DHN.
author2 Xu Yan
author_facet Xu Yan
Chen, Yumin
format Thesis-Master by Research
author Chen, Yumin
author_sort Chen, Yumin
title Multi-energy microgrid optimal operation
title_short Multi-energy microgrid optimal operation
title_full Multi-energy microgrid optimal operation
title_fullStr Multi-energy microgrid optimal operation
title_full_unstemmed Multi-energy microgrid optimal operation
title_sort multi-energy microgrid optimal operation
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/136774
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